Abstract: :
Purpose: Array analysis is a powerful tool for identifying geneexpression and event changes. A major problem in the utilizationof membrane macroarrays is the inability to control intermembranevariation, which results in a high false positive identificationrate. One advantage of macroarrays is that they are reusable,unlike glass chip microarrays. We report on a method for directnormalization of different macroarray membranes, to enable optimizationof retinal aging data obtained by this method from multiplemembranes.Methods: Human donor tissues were obtained using an approvedIRB exemption protocol. GDA ver. 1.3 human cDNA arrays (N=6)(Invitrogen)with 18,376 double spotted ESTs were reacted with equivalentamounts of 33P radiolabeled cDNA probe generated from totalRNA from a single human brain (visual cortex). Membranes wereprehybridized, hybridized and stringently washed according tomanufacturers recommended protocols, and exposed to a phosphorimagingscreen (Kodak) for three days, imaged (molecular dynamics),and membrane spot information translated using commercial technology(Brinervision). Membranes were also exposed to autoradiographicfilm (Kodak Biomax). Following radiodecay (10 months), membraneswere reacted with RNA from individual human donor samples; 3young and 3 old. Experimental data for each spot was normalizedfor each membrane based on the brain cDNA control.Results: Wide variation occurred in intensity between membranes,for every spot. Single probe normalization enabled identificationof a minimal subset of genes that are candidates for age–relatedchanges. Eliminating ESTs by cutoff signal (200 CPM/young) reducedtotal EST number to 5440 (29.6% total). 554 (10%) ESTs wereexpressed at 2–fold or greater in old vs. young. TheseESTs included alcohol dehydrogenase–6 and melanoma–1antigen. In contrast, 3188 (59% or ∼6 fold more) ESTs were expressedat 2 fold or greater levels in young vs. old. ESTs preferentiallyexpressed in young individuals included calbindin–2, anti–elastaseand BCL–2. However, common controls such as GAPDH showedwide variation between samples.Conclusions:Despite array optimization, wide variation existsin array analysis using human donor tissue samples. These variationsare likely due to multiple variables. Results obtained by poolingeven moderate array sample numbers likely over–estimatethe total overall genes changing during aging. Results obtainedfrom human tissues must be confirmed by statistically validnumbers and multiple methodologies.